Remote Sensing in Natural Hazard Monitoring

1
Remote Sensing in Natural Hazard Monitoring

• Bruce H. Ramsay, William Y. Tseng , George
  Stephen, Robert Fennimore, and Fernando
  Sotelo
• NOAA/NESDIS, Washington, D.C. 20233, USA
• Litton PRC, GOES Data Distribution System
  Support Contractor, Washington, D.C. 20233, USA

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Table of Contents

• Introduction
• OSEI Purpose
• Support Policies
• Defining a Natural Hazard/Significant Event
• The Process
• Identification of Significant Events
• Notification Protocols
• The Acquisition of Imagery
• The Analysis of Imagery
• The Production of Imagery
• Quality Control

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Table of Contents (Contd)

• Storage and Dissemination of Data
• Website Control and File Management
• The Daily Report
• Recent Event Supports and Examples

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Introduction

• OSEI Purpose
• To produce and analyze remotely sensed imagery,
  in near real-time, from satellite sensors, for
  the identification and monitoring of short-term
  natural and anthropogenic hazards.
• Imagery available in NOAA NOAA-AVHRR, GOES, GMS,
  DMSP-SSM/I, TOMS-EP, METEOSAT, RADARSAT SAR, and
  SeaWiFS
• Support Policies
• Operational support
• All locations in the world
• Near real-time and quick turn around after an
  event

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Introduction (Contd)

• Defining a Natural Hazard/Significant Event
• Significant depends upon ones point of view.
• Significant Events are defined not just in
  context with situations which produce spectacular
  remotely-sensed images, but also with those that
  have a severe impact to lives and property.
• Typical Significant Events Fires, Smoke,
  Volcanic Eruptions and Ash Plumes, Tropical
  Cyclones, Floods, Oil Spills, Snow Cover or Ice,
  Dust Storms, Tornado Outbreaks, Storms, and Red
  Tides.

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The Process

• Identify Significant Events
• Define Significance and Classify the
  Significance Threshold (ST) from ST0 (lowest)
  to ST3 (highest).
• Notify the OSEI Team Members
• Acquire, Analyze and Produce Imagery
• Quality Control
• Store, Disseminate and Archive Data
• Daily Operational Significant Event Support Report

7
Recent Event Supports and Examples

• Fires Southeast Asia, Australia, Brazil, Canada,
  Central America, Guyana, Indonesia, Mexico, the
  Philippines, and the United States
• Dust Africa, East Asia, MidEast and the Pacific
  Ocean
• Floods Afghanistan, Argentina, Kenya, Pakistan,
  Peru, Somalia, and the United States
• Snow Cover or Ice The Antarctic, and the Arctic,
  Canada, and the United States

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Recent Event Supports and Examples (Contd)

• Storms, Tornado, or Tropical Cyclones Canada,
  Europe, Japan, India, Russia and Georgia, the
  Philippines, the United States, etc.
• Smoke SE Asia, Japan, South America, Italy, and
  the United States
• Volcanic Eruptions Hawaii, Soufriere Hills,
  Kamchatka Peninsula (near Bering Sea),
  Montserrat, Pavlof, and El Arenal (in Costa Rica)
• Oil Spills Coastal oceans off Pakistan, Japan,
  and Paraguay
• Red Tides Hong Kong

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Future Plans

• Implement 7X24 support.
• Implement list serve capability.
• Develop automate data acquisition/event
  identification/classification system - Hazard
  Mapping System (HMS).
• Develop a simple and more friendly image
  processing software.

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Discussion and Conclusion

• All imagery supports are emphasized on the
  operational objective, rather than on the
  scientific purpose.
• Since the turn-around time of imagery support for
  an event is about three hours, a detailed study
  of the imagery is impossible. Therefore, a bias
  in the event location and reality is inevitable.

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Discussion and Conclusion (Contd)

• Ground truth data are usually not available when
  the imagery is issued and disseminated to the
  customer.
• The imagery support, however, has still been
  proved to be a very useful, economical, and
  effective method for identifying and monitoring
  larger-scaled events.